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Simulating Quantum Error Correction beyond Pauli Stochastic Errors

arXiv Quantum Archived Mar 20, 2026 ✓ Full text saved

arXiv:2603.18457v1 Announce Type: new Abstract: Quantum error correction (QEC), the lynchpin of fault-tolerant quantum computing (FTQC), is designed and validated against well-behaved Pauli stochastic error models. But in real-world deployment, QEC protocols encounter a vast array of other errors -- coherent and non-Pauli errors -- whose impacts on quantum circuits are vastly different than those of stochastic Pauli errors. The impacts of these errors on QEC and FTQC protocols have been largely

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    Quantum Physics [Submitted on 19 Mar 2026] Simulating Quantum Error Correction beyond Pauli Stochastic Errors Jordan Hines, Corey Ostrove, Kenneth Rudinger, Stefan Seritan, Kevin Young, Robin Blume-Kohout, Timothy Proctor Quantum error correction (QEC), the lynchpin of fault-tolerant quantum computing (FTQC), is designed and validated against well-behaved Pauli stochastic error models. But in real-world deployment, QEC protocols encounter a vast array of other errors -- coherent and non-Pauli errors -- whose impacts on quantum circuits are vastly different than those of stochastic Pauli errors. The impacts of these errors on QEC and FTQC protocols have been largely unpredictable to date due to exponential classical simulation cost. Here, we show how to accurately and efficiently model the effects of coherent and non-Pauli errors on FTQC, and we study the effects of such errors on syndrome extraction for surface and bivariate bicycle codes, and on magic state cultivation. Our analysis suggests that coherent error can shift fault-tolerance thresholds, increase the space-time cost of magic state cultivation, and can increase logical error rates by an order of magnitude compared to equivalent stochastic errors. These analyses are enabled by a new technique for mapping any Markovian circuit-level error model with sufficiently small error rates onto a detector error model (DEM) for an FTQC circuit. The resulting DEM enables Monte Carlo estimation of logical error rates and noise-adapted decoding, and its parameters can be analytically related to the underlying physical noise parameters to enable approximate strong simulation. Comments: 11 pages+Appendices, 5+3 figures Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2603.18457 [quant-ph]   (or arXiv:2603.18457v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2603.18457 Focus to learn more Submission history From: Jordan Hines [view email] [v1] Thu, 19 Mar 2026 03:39:43 UTC (1,728 KB) Access Paper: HTML (experimental) view license Current browse context: quant-ph < prev   |   next > new | recent | 2026-03 References & Citations INSPIRE HEP NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Quantum
    Category
    ◌ Quantum Computing
    Published
    Mar 20, 2026
    Archived
    Mar 20, 2026
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